Jon

jon@maggylondon.com · Admin · maggylondon.com · ← all users

Active hours

0.18

real mouse/keyboard time

Active days

Sessions

Brands touched

Profiles touched

Pages touched

Daily

Day	Sessions	Active min	Active hours
2026-06-23	7	7.7	0.13
2026-06-24	3	3.1	0.05

Brands

Brand	Owner	Role	Sessions	Active min
Maggy London Women's Dresses	jon@maggylondon.com	Admin	10	10.8

Pages

Page	Report	Sessions	Active min
Amazon Targeting 360	targeting_360	6	7.6
Amazon Automated Master Rules	rule_automation	1	1.3
Amazon Master Overview	master_overview	1	1.3
Profile	other	1	0.4
Logout	other	1	0.2

Actions

Category	Action	Actions	Entities
budget	campaign_budget_updated	18	18
rule	rule_based_created	14	14
scheduler	dayparting_scheduler_created	2	2
rule	rule_based_updated	1	1
scheduler	dayparting_scheduler_updated	1	1

5 queries · scanned 5.72 MB · cost $0.000034 · 7.18s

Query 1 · 1 rows · 2.05 MB · $0.000012 · 1.41s

SELECT
  i.email,
  ANY_VALUE(i.full_name)                              AS full_name,
  ANY_VALUE(i.email_domain)                           AS email_domain,
  ANY_VALUE(s.role)                                   AS role,
  COUNT(DISTINCT i.day)                               AS active_days,
  ANY_VALUE(s.brands_touched)                         AS brands_touched,
  ANY_VALUE(s.profiles_touched)                       AS profiles_touched,
  ANY_VALUE(s.pages_touched)                          AS pages_touched,
  SUM(s.sessions)                                     AS sessions,
  SUM(i.sum_active_seconds)                           AS active_seconds,
  ROUND(SUM(i.sum_active_seconds)/3600.0, 2)          AS active_hours
FROM `amazoneast.customerio_data.fact_session_intervals_daily` i
LEFT JOIN (
  SELECT day, email, SUM(sessions) AS sessions, ANY_VALUE(role) AS role,
         COUNT(DISTINCT brand_group) AS brands_touched,
         COUNT(DISTINCT profile_id)  AS profiles_touched,
         COUNT(DISTINCT report_page) AS pages_touched
  FROM `amazoneast.customerio_data.fact_sessions_daily`
  WHERE day BETWEEN DATE '2026-06-17' AND DATE '2026-06-24'
    AND LOWER(email) = LOWER('jon@maggylondon.com')
  GROUP BY day, email
) s USING (day, email)
WHERE i.day BETWEEN DATE '2026-06-17' AND DATE '2026-06-24'
  AND LOWER(i.email) = LOWER('jon@maggylondon.com')
GROUP BY i.email

Query 2 · 2 rows · 895.2 KB · $0.000005 · 1.39s

SELECT i.day,
       s.sessions,
       ROUND(i.sum_active_seconds/60.0, 1) AS active_min,
       ROUND(i.sum_active_seconds/3600.0, 2) AS active_hours
FROM `amazoneast.customerio_data.fact_session_intervals_daily` i
LEFT JOIN (
  SELECT day, SUM(sessions) AS sessions
  FROM `amazoneast.customerio_data.fact_sessions_daily`
  WHERE LOWER(email) = LOWER('jon@maggylondon.com')
    AND day BETWEEN DATE '2026-06-17' AND DATE '2026-06-24'
  GROUP BY day
) s USING (day)
WHERE LOWER(i.email) = LOWER('jon@maggylondon.com')
  AND i.day BETWEEN DATE '2026-06-17' AND DATE '2026-06-24'
ORDER BY i.day

Query 3 · 1 rows · 1.46 MB · $0.000009 · 1.40s

SELECT brand_group,
       ANY_VALUE(profile_owner_email) AS profile_owner_email,
       ANY_VALUE(role)                AS role,
       SUM(sessions)                  AS sessions,
       ROUND(SUM(active_seconds)/60.0, 1) AS active_min
FROM `amazoneast.customerio_data.fact_sessions_daily`
WHERE LOWER(email) = LOWER('jon@maggylondon.com')
  AND day BETWEEN DATE '2026-06-17' AND DATE '2026-06-24'
GROUP BY brand_group
ORDER BY active_min DESC

Query 4 · 5 rows · 1.27 MB · $0.000008 · 1.43s

SELECT report_page,
       ANY_VALUE(report)                  AS report,
       SUM(sessions)                       AS sessions,
       ROUND(SUM(active_seconds)/60.0, 1)  AS active_min
FROM `amazoneast.customerio_data.fact_sessions_daily`
WHERE LOWER(email) = LOWER('jon@maggylondon.com')
  AND day BETWEEN DATE '2026-06-17' AND DATE '2026-06-24'
GROUP BY report_page
ORDER BY active_min DESC
LIMIT 5000

Query 5 · 5 rows · 70.7 KB · $0.000000 · 1.56s

SELECT action_category,
       action_type,
       SUM(action_count)      AS actions,
       SUM(entity_count)      AS entities
FROM `amazoneast.customerio_data.fact_actions_daily`
WHERE LOWER(email) = LOWER('jon@maggylondon.com')
  AND day BETWEEN DATE '2026-06-17' AND DATE '2026-06-24'
GROUP BY action_category, action_type
ORDER BY actions DESC